Details

Autor(en) / Beteiligte

• Dao, Fu-Ying
• Lv, Hao
• Zhang, Dan
• Zhang, Zi-Mei
• Liu, Li
• Lin, Hao

Titel

DeepYY1: a deep learning approach to identify YY1-mediated chromatin loops

Ist Teil von

• Briefings in bioinformatics, 2021-07, Vol.22 (4)

Ort / Verlag

Oxford: Oxford University Press

Erscheinungsjahr

2021

Quelle

EBSCOhost Business Source Ultimate

Beschreibungen/Notizen

• Abstract The protein Yin Yang 1 (YY1) could form dimers that facilitate the interaction between active enhancers and promoter-proximal elements. YY1-mediated enhancer–promoter interaction is the general feature of mammalian gene control. Recently, some computational methods have been developed to characterize the interactions between DNA elements by elucidating important features of chromatin folding; however, no computational methods have been developed for identifying the YY1-mediated chromatin loops. In this study, we developed a deep learning algorithm named DeepYY1 based on word2vec to determine whether a pair of YY1 motifs would form a loop. The proposed models showed a high prediction performance (AUCs$\ge$0.93) on both training datasets and testing datasets in different cell types, demonstrating that DeepYY1 has an excellent performance in the identification of the YY1-mediated chromatin loops. Our study also suggested that sequences play an important role in the formation of YY1-mediated chromatin loops. Furthermore, we briefly discussed the distribution of the replication origin site in the loops. Finally, a user-friendly web server was established, and it can be freely accessed at http://lin-group.cn/server/DeepYY1.